ALS, Google, Asia Online, and Others at TAUS Round Table, Moscow
Milpitas, May 28, 2014 — May 22nd saw the first
Automated translation technologies help businesses to improve dramatically the productivity of language specialists while optimizing translation processes in general. The most well-known technologies of this type are CAT (Computer-Aided Translation) and machine translation (MT). Reasonable and competent usage of MT systems helps reduce the time and costs required for translation (Fig. 1).
The round table was organized by ALS, the global provider of linguistic services and technologies, and TAUS, a large international resource center in the field of translation automation.
What we’ve learned from this event is how people across the globe have changed their attitude towards translation automation technologies: overall competency has greatly increased, and there are new cloud opportunities challenging the professionals all over the globe now.
Experts from Google, Asia Online, Yandex, ALS, and other industry players have discussed possibilities of translators’ collaboration in real time, efficient use of machine translation, computer-aided solutions, and many other innovations brought to life by flexible and feature-rich cloud services for the translation industry.
However, the major topic of discussion was machine translation, especially post-editing approaches for MT.
“We are actively and constantly working on our post-editing processes for machine translation. The major know-how is that our own specialists are developing all the automation tools we need. For example,
“At Yandex, we are leveraging machine translation widely,» says Farkhat Aminov, Project Manager at the Language Technologies Department of Yandex. «Machine translations are primarily demanded in our internal localization projects, as well as by partner companies and hundreds of thousands of our end users, who often translate their private e-mails, descriptions of products in online shops outside Russia, and also lots of learning materials.”
Participants of the round table also touched on quality assurance. Maxim Lobanov of Google talked about the readability of translations during the QA procedures and how this important criterion correlates to the remaining five types of errors used in quality assessment of machine translations at Google.
Jaap van der Meer, the founder of TAUS, said that “The translation industry is now shifting into top gear from tens of thousands of customers, who used to think of translation as a premium product, to six billion users looking forward to getting free-of-charge translations. As for our industry in general, it is time to give serious thought to innovation technologies, social changes, future challenges, and advanced monetization models.”
TAUS Round Table saw renowned experts and experienced specialists in translation automation, language service providers and their customers, independent translators, technical writers, university representatives, and more. Apart from the spokespeople, many guests from various companies, including Acronis, iiko, Siemens, Ernst & Young, Baker & McKenzie, also showed great interest in the discussion.
Figure 1. The average productivity gain in various production scenarios
The diagram illustrates the post-editing performance of machine translation in the following scenarios: human translation, machine translation with post-editing without preliminary system setup, machine translation with post-editing and preliminary system setup powered by a term base and a corpus of parallel texts. Source: internal survey conducted by ALS.
ALS is a global language technology partner and service provider.
ALS provides comprehensive language support to more than 2,500 companies worldwide and helps streamline multilingual content maintenance by means of translation workflow automation and cutting-edge linguistic solutions. The company’s offering for the translation automation industry includes cloud-based translation platform SmartCAT.Ai, cloud-based terminology management solution Lingvo.Pro, machine translation technologies and enterprise or domain-specific MT engines, advanced crowdsourcing translation solutions and much more.
The company’s advanced technological background is ensured by being a part of ABBYY Group (www.abbyy.com) — a leading provider of document recognition, data capture, and linguistic products with more than 30 million users in over 150 countries and one of the largest global research centers in language technologies.